The present invention relates to a method of automatically performing, for individual internal organs, a region extraction processing (hereinafter the region extraction processing for individual internal organs will be referred to as "internal organ extraction") needed as Pre-processing when each internal organ is displayed three-dimensionally by using in-body image data, especially, a tomography image which is imaged three-dimensionally.
In order to display a specified internal organ three-dimensionally, the internal organ must first be extracted from image data. However, any method of performing the internal organ extraction automatically has not been established yet and for accurate extraction, a contour of the internal organ must be inputted manually for each slice image. However, the amount of three-dimensional data is very large and therefore, in the clinical setting requiring real time performance, the manual internal organ extraction is unpractical.
Two approaches to the general method for region extraction have been contrived including:
(1) A method of tracking the contour of a region of interest (hereinafter abbreviated as an ROI) PA1 (2) A method of Performing the region expansion by starting from a point inside an ROI.
The method in item (1) above is for automatically tracking the contour of an internal organ by looking up a local density difference of an image and has hitherto been used widely in the medical image processing. An example of this method is discussed in Radiology, Vol. 171, No. 1, April 1989, pp. 277-280. This type of method of tracking one line is however, liable to be fatally affected by noise and artifacts, facing a problem of impairment of reliability. In addition, the method is carried out by merely processing the slice sheet by sheet and fails to effectively utilize data of three-dimensional structure.
The method in item (2) above is for extracting an ROI by first selecting a certain point inside the ROI, retrieving a point connecting to the selected point from adjoining pixels, and taking in the connected point to expand the ROI. In general, this method is called region growing and referred to in Digital Picture Processing by Azriel Rosenfeld, pp. 334-335. Typically used as the condition for deciding the connection (hereinafter referred to as the expansion condition) is the difference between average density over the entire region and density of a tracking point. The prior art method finds many applications to, for example, character pattern extraction but is difficult to apply to the internal organ extraction because good results can not be obtained when the method is applied by simply using the above condition for medical images having sophisticated forms and density changes.